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System dynamics of urban traffic based on its parking-related-states

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  • Cao, Jin
  • Menendez, Monica

Abstract

The urban parking and the urban traffic systems are essential components of the overall urban transportation structure. The short-term interactions between these two systems can be highly significant and influential to their individual performance. The urban parking system, for example, can affect the searching-for-parking traffic, influencing not only overall travel speeds in the network (traffic performance), but also total driven distance (environmental conditions). In turn, the traffic performance can also affect the time drivers spend searching for parking, and ultimately, parking usage. In this study, we propose a methodology to model macroscopically such interactions and evaluate their effects on urban congestion.

Suggested Citation

  • Cao, Jin & Menendez, Monica, 2015. "System dynamics of urban traffic based on its parking-related-states," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 718-736.
    • Handle: RePEc:eee:transb:v:81:y:2015:i:p3:p:718-736
    DOI: 10.1016/j.trb.2015.07.018
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Gu, Ziyuan & Li, Yifan & Saberi, Meead & Rashidi, Taha H. & Liu, Zhiyuan, 2023. "Macroscopic parking dynamics and equitable pricing: Integrating trip-based modeling with simulation-based robust optimization," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 354-381.
    3. Xu, Zhengtian & Yin, Yafeng & Zha, Liteng, 2017. "Optimal parking provision for ride-sourcing services," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 559-578.
    4. Pei Liu & Dong Mu & Daqing Gong, 2017. "Eliminating Overload Trucking via a Modal Shift to Achieve Intercity Freight Sustainability: A System Dynamics Approach," Sustainability, MDPI, vol. 9(3), pages 1-24, March.
    5. Cao, Jin & Menendez, Monica, 2018. "Quantification of potential cruising time savings through intelligent parking services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 151-165.
    6. Jia Shi & Xuesong Guo & Xiangnan Hu, 2019. "Engaging Stakeholders in Urban Traffic Restriction Policy Assessment Using System Dynamics: The Case Study of Xi’an City, China," Sustainability, MDPI, vol. 11(14), pages 1-16, July.
    7. Paipuri, Mahendra & Leclercq, Ludovic, 2020. "Bi-modal macroscopic traffic dynamics in a single region," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 257-290.
    8. Yang, Kaidi & Roca-Riu, Mireia & Menéndez, Mónica, 2019. "An auction-based approach for prebooked urban logistics facilities," Omega, Elsevier, vol. 89(C), pages 193-211.
    9. Pel, Adam J. & Chaniotakis, Emmanouil, 2017. "Stochastic user equilibrium traffic assignment with equilibrated parking search routes," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 123-139.
    10. Mariotte, Guilhem & Leclercq, Ludovic, 2019. "Flow exchanges in multi-reservoir systems with spillbacks," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 327-349.
    11. Leclercq, Ludovic & Sénécat, Alméria & Mariotte, Guilhem, 2017. "Dynamic macroscopic simulation of on-street parking search: A trip-based approach," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 268-282.
    12. Zakharenko, Roman, 2016. "The time dimension of parking economics," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 211-228.
    13. Gu, Ziyuan & Safarighouzhdi, Farshid & Saberi, Meead & Rashidi, Taha H., 2021. "A macro-micro approach to modeling parking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 220-244.

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